1. Field of the Invention
The present invention relates to a noise estimation method and apparatus, and more particularly, to a method and apparatus to effectively reduce noise by estimating the noise when a video signal distorted by the noise is input to a video encoder based on motion compensation (MC) and a discrete cosine transform (DCT), for example an encoder, such as a moving picture experts group (MPEG)-2 or MPEG-4 encoder.
2. Description of the Related Art
Recently, receivers, such as set-top boxes and other products that receive analog ground wave broadcasting have been introduced, which use a compression method, such as the MPEG-2 or MPEG-4, to encode and store the broadcasting. However, image signals that are input to the receiver are frequently distorted by a variety of noises, including white Gaussian noise, caused by transmission channels.
For example, an entire image signal is distorted by the variety of noises, including the white Gaussian noise. If the image signal is compressed as is, the compression efficiency is degraded due to the noises.
Accordingly, much research on ways to reduce the noise in the image signals has been performed. However, conventional methods to reduce the noise basically assume that a degree of noise is known to some extent, and, accordingly, a variety of methods for estimating noise are employed.
An example of these noise estimation methods is disclosed in European Patent No. 0712554.
Referring to FIG. 1, a conventional method to reduce the noise will now be explained.
FIG. 1 is a block diagram showing a conventional noise estimation apparatus. The conventional noise estimation apparatus includes a first subtractor 112, a frame memory 114, a first absolute value calculator 116, a first low pass filter 118, a second low pass filter 120, a second subtractor 122, a second absolute value calculator 124, a third subtractor 126, a third absolute value calculator 128, an adder 130, and a noise quantity estimation unit 132.
First, the first subtractor 112 calculates a first difference value between two neighboring pictures, based on a current input picture and a neighboring picture from the frame memory 114. The calculated difference value between the neighboring pictures is input to the first absolute value calculator 116. The first absolute value calculator 116 calculates an absolute value of the difference value calculated in the first subtractor 112 and outputs a result indicative thereof to the third subtractor 126.
Meanwhile, the second subtractor 122 calculates a second difference value between the current input picture, which is input through the first low pass filter 118, and the neighboring picture which is input through the second low pass filter 120. The calculated difference value, which is low pass filtered, is input to the second absolute value calculator 124. The second absolute value calculator 124 calculates the absolute value of the second difference value calculated in the second subtractor 122 and outputs a result indicative thereof to the third subtractor 126.
The third subtractor 126 calculates a third difference value of the inputs from the first absolute value calculator 116 and the second absolute value calculator 124, and inputs the calculated difference value to the third absolute value calculator 128. The third absolute value calculator 128 calculates the absolute value of the third difference value calculated in the third subtractor 126, and outputs a result indicative thereof to the adder 130.
The adder 130 adds the absolute value, which is output from the third absolute value calculator 128, in units of frames.
The noise quantity estimation unit 132 determines a quantity of noise included in the input picture, based on the value obtained by the adder 130.
If the value calculated in units of frames by the adder 130 is large, the conventional noise estimation apparatus 100 determines that there is a large amount of noise, and if the value is small, the conventional noise estimation apparatus 100 determines that there is a small amount of noise.
However, though the conventional noise estimation apparatus can estimate noise in an almost motionless picture, the output value of the adder 130 becomes greater due to motion in a moving picture. Accordingly, it is very difficult to estimate the noise in the moving picture.